Distributed data processing domains are designed to handle mission critical processing of data. Typically, a distributed data processing domain requires multiple data processing nodes that span physical boundaries and work in conjunction to process the data with high availability failover capabilities. For this type of node configuration, it can be essential that local information and global information as contained in domain information files stored on the data processing nodes be consistent across the entire distributed data processing domain in order to provide the high availability failover capabilities. This can be achieved even with an update of one of the domain information files by a timely update synchronization of the remaining domain information files whereby all of the domain information files are identical upon conclusion of the update synchronization. However, update synchronization techniques currently are not designed to result in identical domain information files being stored on each data processing node.
For example, one known update synchronization technique provides a capability of a local data processing node to update and make changes to a file on a domain information file on a remote data processing node via various system calls. The drawback to this technique is the failure to store the domain information file one each data processing node and the requirement that the local data processing node be able to execute the needed system calls.
Another update synchronization technique is premised on the use of owner tokens and data management of volume version numbers whereby version numbers of a particular volume are associated with a current owner of a corresponding token. However, drawbacks to this technique are the failure to store the volumes on each data processing node and a need to interact with a database containing information about the version number(s) of the volumes.